(1) Field of the Invention
The present invention relates to target motion analysis. It provides a means for automated partitioning of a data sequence into "segments" each of which contains data with homogenous characteristics. Boundaries between data segments correspond to likely event times such as changes in the measurement process or shifts in a state parameter description. Automatic segmentation is required for current state-of-the-art target motion analysis algorithms for submarine applications.
(2) Description of the Prior Art
Performance of underwater target motion analysis is contingent upon the ability to partition the measurement sequence into segments each of which is homogeneous in nature. Historically, segments have been delineated using known events such as changes in observer motion or by human intervention such as a computer operator inputting his or her judgment concerning segment boundaries upon observing a display of the data sequence.
Other traditional techniques for automatic data segmentation are typically divisive in nature and initially assume that all measurements within a time series belong together. These techniques examine the time series for features or changes in characterizing parameters which would correspond to segment boundaries. When measurements are made on multiple sources the problem of measurement to source association must be addressed. When it can no longer be assumed that all measurements belong to the same source, the data set must be partitioned according to its origin as well as partitioned in time. A traditional divisive technique is the sliding window approach, which is generally effective for purposes or partitioning in time. However, this technique is not amenable to partitioning according to its origin as well as partitioning in time.